We employ the Lomb-Scargle periodogram method [1]} for detecting and characterizing periodic signals. The Lomb–Scargle periodogram yields an estimate of the Fourier power spectrum \(P(f)\)  at frequency \(f\)  in an unevenly sampled dataset. After getting the power spectrum, we evaluate the signal strength by calculating the signal-to-noise ratio
\(P_{\text{signal }}=\frac{1}{\delta } \int _{f_{w}-\frac{\delta }{2}}^{f_{w}+\frac{\delta }{2}} P(f) df \\\text{\footnotesize $P_{\text{noise }}=\frac{1}{F-\delta }\left[\int _{0}^{f_{w}-\frac{\delta }{2}} P(f) d f+\int _{f_{w}+\frac{\delta }{2}}^{F} P(f) d f\right]$} \\P_{\text{snr}}=P_{\text{signal }} / P_{\text{noise }},\) 
